Tag Archives: loyalty analytics

In my last post I described a set of analytics projects that drive real competitive advantage in retail and eCommerce. These projects are meant to be the opening of the third and final stage of an analytically driven digital transformation. They are big, complex, important projects that make a real difference to the way the business works.

But I know folks outside retail (and they’re the majority of my client-base) get frustrated because so much of the analytics technology and conversation seems to reflect retail concerns. So in this post, I wanted to describe an alternative set of projects specifically for another industry (I picked Hospitality) and talk a little bit about some of the key analytics flashpoints in different industries. Every business is unique. There is no one right set of projects when you get to this phase of digital transformation, but there are analytics projects that are quite important to almost everyone in a given industry.

Here’s a fairly generic set of projects I’d typically attach to a presentation on digital transformation in hospitality. You can see that about half the projects are the same as what I recommended for retail.

Aggressive personalization is a core part of MOST good digital programs – almost regardless of industry. If you’re in health-care, financial services, retail, travel & hospitality, government or technology, then analytics-driven personalization should be a high priority. It’s actually a lot easier to say where personalization might not be near the top of the list: CPG and maybe manufacturing. In CPG, many web sites are too shallow and lack enough interesting content to make personalization effective. In fact, the Website itself is often pretty unimportant. CPG folks should probably be more worried about their marketing and social media analytics than personalization. Manufacturers might be on the same level, but a lot depends on the type of industry, how many products you have, how many audiences, and how much content. In every case, the more you have (product, audience, content), the more likely it is that personalization should be a strategic priority.

I also included Surprise-based Loyalty. Travel is actually the sector where I first developed these concepts. You can read a somewhat more detailed explanation in an article I recently published in the CIO Outlook for Travel & Hospitality. But there are quite a few reasons why hospitality, in particular, is a great place to build a surprise-based program. First, the hospitality industry has numerous opportunities to deliver surprise-based loyalty at little or no cost. That’s critical. Hospitality also has the requisite data to allow for powerful analytic targeting and has sufficient touches to make the concept powerful and workable. What’s more, most of the rewards programs in hospitality suffer from scale. Sure, a few global giants have the reach to make a traditional loyalty program appealing. But if you’re a boutique or mid-tier chain, your traditional loyalty program will never look particularly attractive. Surprise-based concepts get around all that. With no fixed cost, the ability to target and grow them organically, and real impact on loyalty, they deliver a fundamentally different kind of experience that doesn’t depend on scale and global reach.

My third project is another one that could appear almost everywhere: mobile optimization. For Hospitality, it’s particularly important to create a great mobile on-property experience and build out the mobile experience as the Hub for loyalty. Integration of mobile digital experiences with property systems enables a whole array of real experience difference makers – room selection, automatic upgrading, room bidding, expedited check-in, door control, service requests and, of course, plenty of surprise (and traditional) loyalty opportunities.

Why didn’t this show up in retail? Hey, it could. It might be sixth on my generic list. But many of the retailers I’m working with are struggling to figure out how to make mobile an important part of the experience. With all the beaconing and wifi we’ve seen, most opt-in systems simply don’t get enough adoption to make them worthwhile. I think it’s easier to drive adoption in hospitality. And adoption is critical to driving serious advantage.

When I talk about advanced Revenue Management I’m clearly hovering somewhere on the edge of what might reasonably be considered digital. There are lots of different ways to improve revenue management, but what I have in mind here are two specific types of analysis. The first is using digital view volume to feed demand signals into revenue management. This is a simple but effective technique for taking advantage of your digital data to improve your price planning. I also believe that in the zero-sum game that is room (and flight) planning, there are opportunities to use digital data collection from OTAs to reverse engineer competitor pricing strategies and then optimize your price curve to take advantage of that knowledge.

In retail, I talked about the growing importance of electronic signage and integrated digital experiences and optimizing the measurement of those (largely unmeasured) systems. In Hospitality, I’ve picked something that isn’t quite the same but falls in the same omni-channel category – optimizing the integration of on-property with digital. This cuts in both directions and overlaps with the analytics around mobile (obviously), personalization (obviously), surprise-loyalty (obviously) and revenue management. Revenue Management a little less obviously but most revenue management systems use time-based pricing not customer based pricing – often completely missing differentials in customer value from on-property behavior. Casino’s, of course, are the exception to this.

For resort properties, there are significant opportunities to integrate digital view behavior into on-property drives. But for almost every type of property there are ways to make the on-property experience better. Some of this is ridiculously easy. When I log into my hotel wifi, I almost always get the standard property page. No customization. No personalization. But I’m a heavy consumer of certain types of on-property experiences including some highly-profitable ones like late-night room service dinners. Do I ever get a dinner drive? A special offer? A loyalty treat? Nope. Pretty much never.

I put this digital/on-property integration high on the list mostly because when it comes to hospitality, the on-property experience is THE critical factor. I might love or hate the Website or even the App, but both are just little bumps on the great big behind that is the actual stay. If I can help make the stay experience better with digital, I’ve done something important.

So my top five projects for hospitality are:

Personalization

Surprise-based Loyalty

Digital Additions to Revenue Management

Mobile Experience and Loyalty Optimization

On-Property digital integration

As with retail, none are easy. Most involve complex integrations AND deep analytics to work well. But they form a powerful and powerfully related nexus of programs that drive real competitive advantage.

Of course, as I’ve tried to make clear, the selection of a top-five is utterly arbitrary. Every business will have its unique strategic priorities, market position, and brand. Those things matter. What’s more, the third phase of an analytics transformation is open-ended. There aren’t just five things. You don’t stop when (if ever) you’ve done these projects.

So it’s natural to ask what are some other commonly important projects that didn’t make the list (and weren’t already captured in the earlier two phases). Here, with some notes about industries, are some more things to chew on:

Digital Acquisition Optimization (Campaign-level): I’ve already covered both a campaign measurement framework and Mix/Attribution in the first two phases. But I haven’t been quite true to myself since I often tell clients to worry about optimizing your individual channels and campaigns first before you worry about attribution. There are more powerful analytic techniques for campaign-specific optimization than attribution – and many, many enterprises would be well-advised focus on those techniques as part of their overall digital transformation. I won’t say that every digital media buy I see sucks. But a lot do. This one isn’t specific to industry; it’s important to anyone dropping significant dime on digital marketing.

Right-Channeling Support: This analytics project often makes my top-five list in financial services, technology, and health care (but it’s important in a lot of other places too). Not only is the call-center a significant cost for many an enterprise, it’s almost always a significant driver of churn and bad experience. That’s not always because call-centers are bad – it’s hard to do well. And these days, many people (I’m certainly in this bucket) flat out prefer digital servicing in most use-cases. So digital servicing is a big deal and it’s deeply analytic. Bridging digital and call is a huge analytics opportunity and one of the most important projects you can take in a digital transformation.

Digital Sales Support: If a field-sales force is a core part of your business, then digital analytics to support what they do is often in my top-five projects around transformation. Technology, Pharma, and certain areas of Financial Services (like Insurance and Wealth) all need to figure out how their digital assets play with their field sales force. Siloed approaches here are worse than silos in digital marketing attribution. You can NOT do this well unless you tackle it as an integrated effort with consistent measurement across the journey.

Content Attribution: When I was at the Digital Analytics Hub in Europe one of the most interesting parts of the discussion around transformation focused on the need for traditional companies to become, in effect, media companies. There’s nothing terribly original about this idea (not sure who’s it is), but it is terribly important and often it’s a huge stumbling block when it comes to transformation. Companies don’t build nearly enough content to be good at digital and they don’t measure it appropriately. Learning how to measure the content experience and how to take advantage of content are keys to effective digital transformation and anyone focused on building deeper sales cycles should think carefully about making content attribution a prominent part of their initial analytics plan.

Balancing Success: One of the biggest failure points in digital transformation in my client-base involves situations where a digital property has several very important enterprise functions. Selling and generating leads, advertising and engagement, linear vs. direct consumption, building brands vs. generating revenue. These are all common examples. The problem is that most enterprises are wishy-washy when it comes to balancing these objectives. When I ask senior folks what they really want (or when I look at how people are measured), what I usually hear is both. That’s not helpful. There are analytic approaches to measuring the trade-offs in site real-estate and marketing between driving to multiple types of success. If you haven’t done the analytics work to figure this out and set appropriate incentives and performance measurements, you’re simply not going to be good at all – and perhaps any – of your core functions.

Well, I could go on of course. But I’m almost at four pages now – which I know is excessive. There are a lot of options. That’s why creating a strategic plan for analytics transformation isn’t trivial and it isn’t boilerplate. But as I pointed out in my introduction to the last post, this is the fun stuff.

In my next post, I hope to tackle those organizational issues I’ve been deferring for so long – but I may have one or two more detours up my sleeve!

People have struggled with this (big) data provider model but Factual feels like it’s found a real (and valuable) niche. Would love to see more of this grow since external data is a huge miss in most big data systems.

Targeted VoC is a powerful (and totally neglected) tool for personalization. Facebook’s experience is entirely relevant to ANY content producer. I don’t know if I can take credit for this, but I suggested this to folks at Facebook a couple of years back!

An interesting discussion of the problems in identifying “likely” voters and the benefits of behavioral data integration. Food for thought in the enterprise world as well where the equivalent is often possible but rarely done.